Binary classification with corrupted labels
Binary classification with corrupted labels
In a binary classification problem where the goal is to fit an accurate predictor, the presence of corrupted labels in the training data set may create an additional challenge. However, in settings where likelihood maximization is poorly behaved—for example, if positive and negative labels are perfectly separable—then a small fraction …